{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np # 导入Numpy\nimport pandas as pd # 导入Pandas\nfrom sklearn import datasets # 导入sklearn的数据集\niris = datasets.load_iris() # 导入iris\nX_sepal = iris.data[:,[0,1]] # 花萼特征集：两个特征长和宽\nX_petal = iris.data[:,[2,3]] # 花瓣特征集：两个特征长和宽\ny = iris.target # 标签集","execution_count":1,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split # 导入拆分数据集工具\nfrom sklearn.preprocessing import StandardScaler # 导入标准化工具\nX_train_sepal, X_test_sepal, y_train_sepal, y_test_sepal = \\\n  train_test_split(X_sepal,y,test_size=0.3,random_state=0) # 拆分数据集\nprint(\"花萼训练集样本数: \", len(X_train_sepal))\nprint(\"花萼测试集样本数: \", len(X_test_sepal))\nscaler = \tStandardScaler() # 标准化工具\nX_train_sepal = scaler.fit_transform(X_train_sepal) # 训练集数据标准化\nX_test_sepal = scaler.transform(X_test_sepal) # 测试集数据标准化\n# 合并特征集和标签集，留待以后数据展示之用\nX_combined_sepal = np.vstack((X_train_sepal,X_test_sepal)) # 合并特征集\nY_combined_sepal = np.hstack((y_train_sepal,y_test_sepal)) # 合并标签集","execution_count":2,"outputs":[{"output_type":"stream","text":"花瓣训练集样本数:  105\n花瓣测试集样本数:  45\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.linear_model import LogisticRegression # 导入逻辑回归模型\nlr = LogisticRegression(penalty='l2', C = 0.1) # 设定L2正则化和C参数\nlr.fit(X_train_sepal,y_train_sepal) # 训练机器\nscore = lr.score(X_test_sepal,y_test_sepal) # 测试集分数评估\nprint(\"SK-learn逻辑回归测试准确率 {:.2f}%\".format(score*100)) ","execution_count":3,"outputs":[{"output_type":"stream","text":"SK-learn逻辑回归测试准确率 66.67%\n","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt # 导入matplotlib\nfrom matplotlib.colors import ListedColormap # 导入Colormap\ndef plot_decision_regions(X,y,classifier,test_idx=None,resolution=0.02):    \n    markers = ('o','x','v')\n    colors = ('red','blue','lightgreen')\n    color_Map = ListedColormap(colors[:len(np.unique(y))])     \n    x1_min = X[:,0].min() - 1\n    x1_max = X[:,0].max() + 1\n    x2_min = X[:,1].min() - 1\n    x2_max = X[:,1].max() + 1\n    xx1, xx2 = np.meshgrid(np.arange(x1_min,x1_max,resolution),\n                           np.arange(x2_min,x2_max,resolution))    \n    Z = classifier.predict(np.array([xx1.ravel(),xx2.ravel()]).T)\n    Z = Z.reshape(xx1.shape)    \n    plt.contour(xx1,xx2,Z,alpha=0.4,cmap = color_Map)\n    plt.xlim(xx1.min(),xx1.max())\n    plt.ylim(xx2.min(),xx2.max())   \n    X_test, Y_test = X[test_idx,:], y[test_idx]\n    for idx, cl in enumerate(np.unique(y)):\n        plt.scatter(x = X[y == cl, 0], y = X[y == cl, 1],\n                    alpha = 0.8, c = color_Map(idx),\n                    marker = markers[idx], label = cl)","execution_count":4,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import accuracy_score # 导入准确率指标\nC_param_range = [0.01,0.1,1,10,100,1000]\nsepal_acc_table = pd.DataFrame(columns = ['C_parameter','Accuracy'])\nsepal_acc_table['C_parameter'] = C_param_range\nplt.figure(figsize=(10, 10))\nj = 0\nfor i in C_param_range:\n    lr = LogisticRegression(penalty = 'l2', C = i,random_state = 0)\n    lr.fit(X_train_sepal,y_train_sepal)\n    y_pred_sepal = lr.predict(X_test_sepal)\n    sepal_acc_table.iloc[j,1] = accuracy_score(y_test_sepal,y_pred_sepal)\n    j += 1    \n    plt.subplot(3,2,j)\n    plt.subplots_adjust(hspace = 0.4)\n    plot_decision_regions(X = X_combined_sepal, y = Y_combined_sepal, \n                          classifier = lr, test_idx = range(0,150))\n    plt.xlabel('Sepal length')\n    plt.ylabel('Sepal width')\n    plt.title('C = %s'%i)","execution_count":5,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n","name":"stderr"},{"output_type":"display_data","data":{"text/plain":"<Figure size 720x720 with 6 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"lr = LogisticRegression(penalty='l2', C = 10) # 设定L2正则化和C参数\nlr.fit(X_train_sepal,y_train_sepal) # 训练机器\nscore = lr.score(X_test_sepal,y_test_sepal) # 测试集分数评估\nprint(\"Sklearn逻辑回归测试准确率 {:.2f}%\".format(score*100))","execution_count":6,"outputs":[{"output_type":"stream","text":"Sklearn逻辑回归测试准确率 68.89%\n","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n  FutureWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n  \"this warning.\", FutureWarning)\n","name":"stderr"}]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":1}